Decision aids (DAs) provide patients with information about preference sensitive decisions in which patients'preferences are likely to play a key role in determining what the best decision is and allow them more time to process the information than they would in a typical clinical encounter. An international group of experts, the International Patient Decision Aids Standards (IPDAS) Collaboration, has established a list of content that decision aid developers are encouraged to put into DAs. However, it provided no guidance about how to present such content, or how to make sure such content does not create decision biases. Our original grant aimed to identify and reduce cognitive biases created by DAs. We identified multiple cognitive biases that could be created by DAs and have developed several practical techniques for reducing or eliminating these biases. But our work is not done. To extend our accomplishments and respond to the IPDAS recommendations, we are proposing to conduct research targeting several additional biases that are potentially created by DAs and developing techniques to eliminate or reduce them. In addition, we propose to conduct studies that focus not only on the role that cognition plays in people's decisions, but also the role of affect. We thus plan to identify the kind of decision biases likely to arise when patients use decision aids, regardless of whether those biases arise through cognitive or affective processes, and identify ways to reduce them. Specifically, we aim to explore four sources of biases relevant to decision aids: (1) presentation of ambiguous probabilities (2) presentation of contextual information about probabilities (3) people's affective reaction to health outcomes, and (4) people's methods of integrating probability and utility in a single decision. For each source, we will identify multiple factors which bias patient decisions. We propose to identify the scope of each problem, delineate the circumstances under which biases result, and test methods for reducing or eliminating the biases. All our studies will use materials from pre-existing decision aids. Our approach includes two distinct research stages. In the first stage, we use iterative randomized survey experiments to explore which decision aid elements generate bias. We will present people with hypothetical medical decisions, based on material from real decision aids, and vary aspects of the decision task across people, to test hypotheses about how to minimize decision biases. Our initial studies will consider a subset of the relevant factors, and follow-up studies will drill down on factors that are significant in our first experiments and also test additional factors not included due to power and complexity reasons. In the second stage, we will demonstrate the relevance of our first-stage results for patient care. For each source of bias, our research will culminate with a randomized trial of a debiasing technique delivered to a patient population. Relevance Statement Our research aims to improve patient decision aids, which are booklets, websites, or videos that provide patients with information about medical decisions and help them to make the decision that best matches their own preferences. While international standards exist for the content of decision aids, our results will help decision aid developers know how to best present the information in decision aids so as to avoid cognitive and emotional biases. This work is essential to ensuring that patients are fully informed and able to participate in decision making regarding their medical care.